Planar unclustered graphs to model technological and biological networks
Many real life networks present an average path length logarithmic with the number of nodes and a degree distribution which follows a power law. Often these networks have also a modular and self-similar structure and, in some cases - usually associated with topological restrictions- their clustering...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2009 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/2592 |
| Acceso en línea: | https://hdl.handle.net/2117/2592 |
| Access Level: | acceso abierto |
| Palabra clave: | Combinatorics Graphs Networks Complex systems Combinacions (Matemàtica) Circuits Anàlisi de xarxes (Planificació) Classificació AMS::05 Combinatorics Classificació AMS::94 Information And Communication, Circuits::94C Circuits, networks Àrees temàtiques de la UPC::Matemàtiques i estadística |
| Sumario: | Many real life networks present an average path length logarithmic with the number of nodes and a degree distribution which follows a power law. Often these networks have also a modular and self-similar structure and, in some cases - usually associated with topological restrictions- their clustering is low and they are almost planar. In this paper we introduce a family of graphs which share all these properties and are defined by two parameters. As their construction is deterministic, we obtain exact analytic expressions for relevant properties of the graphs including the degree distribution, degree correlation, diameter, and average distance, as a function of the two defining parameters. Thus, the graphs are useful to model some complex networks,in particular technological and biological networks. |
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